The performance of each model in the training and testing datasets is represented by RMSE statistic error.
Each music recording in the aforementioned datasets was represented by three song-level feature vectors, namely the 20-dimensional MFCCs, the 12-dimensional chroma features, and the auditory cortical representations of reduced dimensions.
In this article, the complex left ventricle (LV) shape and motion of 50 RT3datasetsets are represented by novel 4-D descriptors — 4-D sphericity, volume and shape, from which novel indices were derived by principal component analysis (PCA) and subsequently analyzed by a support vector machine (SVM) classifier to assess their capability of LVMD characterization and CRT outcome prediction.
A prerequisite for platform comparison is that all datasets are represented by a common set of probes.
Some strain lineages in our MLSA dataset were represented by fewer strains than other lineages, which could have influenced our analysis.
Applying our DNA barcode method to the same dataset, we observed that 50.36% and 47.52% of this dataset were represented by the Firmicutes and the Bacteroidetes phyla, respectively (Table 3).
After that, the evolution of solutions converges when the near optimal partitioning of the dataset is represented by the fittest solution with the respect of the employed clustering validity index.
In designing the proposed classification method, each class of dataset is represented by a set of sub-graphs (components), and a new extension of the k-associated optimal graph algorithm is introduced in the training phase to combine the smaller components.
To construct the graph, each gene in the dataset is represented by a node.
MicroRNA dataset is represented by i patients (i = 1,..., N) and l miRNAs (l = 1,..., N mi) and gene expression dataset is represented by j patients (j = 1,..., N) and m genes (m = 1,..., N G)).
